It is common in machine vision systems to perform a binary classification of pixels in an image to be analyzed; in other words, one of the values "0" and "1" is assigned to each pixel. Analysis of the image then proceeds on the basis of the binary classification of the pixels.
Since the information making up the image to be analyzed is often presented to the system in non-binary form, such as gray-scale levels, selection of a threshold for binary classification (a "pixel-discrimination threshold") is a fundamental task that must be performed before the analysis of the image. Moreover, it has been found in some machine vision systems, particularly those in which character recognition is to be performed, that the accuracy of the analysis and/or the amount of time required is dependent upon the threshold selected.
An application of machine vision in which setting of a pixel-discrimination threshold has been found to be critical is the automatic recognition of identification codes on semiconductor wafers. The recognition may be performed, for example, for the purpose of sorting or production control, record keeping and the like. FIG. 1 is an illustration of a typical semiconductor wafer, generally indicated by reference numeral 10. The semiconductor wafer 10 is generally planar, and circular in outline except for an indentation in the shape of a segment defined by a straight line edge 12. A multi-character identification code 14 is formed in a surface 16 of semiconductor wafer 10. The characters making up the i.d. code 14 may be formed by laser-etching or a similar process and are arranged in a character line that runs parallel to, and a short distance from, edge 12. The size of the characters as shown in FIG. 1 is not necessarily to scale; in a typical semiconductor wafer 10, the characters may be only a few millimeters high. Further, as will be recognized by those skilled in the art, the surface 16 of semiconductor wafer 10 may have been coated with a metal film or other coating that renders the surface 16 highly reflective. Moreover, although in the illustration the characters are shown as black-on-white, it should be understood that in practice the characters may be evidenced only by impressions in the surface 16, so that there is not a great contrast in tone between the characters of i.d. code 14 and the balance of surface 16.
Adding to the difficulties presented in accomplishing accurate and rapid machine recognition of the i.d. code 14 is the fact that a sequence of wafers bearing i.d. codes to be recognized may include wafers that vary significantly in reflectivity and color.
In setting up a machine vision system for recognition of i.d. code characters, it is often found to be useful to program or otherwise prepare the system to recognize characters having character lines of a predetermined thickness. However, it has been found that the particular pixel-discrimination threshold level used by a machine vision system can have a significant effect on the thickness of the character lines resulting from the binary classification of the pixels. The variations in thickness, in turn, can have a significant adverse effect on one or both of the accuracy of the character recognition and the time required therefor.